An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks
Numerous tiny sensors are restricted with energy for the wireless sensor networks since most of them are deployed in harsh environments, and thus it is impossible for battery re-change. Therefore, energy efficiency becomes a significant requirement for routing protocol design. Recent research introd...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Hindawi - SAGE Publishing
2019-03-01
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1177/1550147719839581 |
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author | Jin Wang Yu Gao Wei Liu Arun Kumar Sangaiah Hye-Jin Kim |
author_facet | Jin Wang Yu Gao Wei Liu Arun Kumar Sangaiah Hye-Jin Kim |
author_sort | Jin Wang |
collection | DOAJ |
description | Numerous tiny sensors are restricted with energy for the wireless sensor networks since most of them are deployed in harsh environments, and thus it is impossible for battery re-change. Therefore, energy efficiency becomes a significant requirement for routing protocol design. Recent research introduces data fusion to conserve energy; however, many of them do not present a concrete scheme for the fusion process. Emerging machine learning technology provides a novel direction for data fusion and makes it more available and intelligent. In this article, we present an intelligent data gathering schema with data fusion called IDGS-DF. In IDGS-DF, we adopt a neural network to conduct data fusion to improve network performance. First, we partition the whole sensor fields into several subdomains by virtual grids. Then cluster heads are selected according to the score of nodes and data fusion is conducted in CHs using a pretrained neural network. Finally, a mobile agent is adopted to gather information along a predefined path. Plenty of experiments are conducted to demonstrate that our schema can efficiently conserve energy and enhance the lifetime of the network. |
first_indexed | 2024-03-12T10:50:48Z |
format | Article |
id | doaj.art-a3b8e497fe1943afb2818fdfa6c4db0b |
institution | Directory Open Access Journal |
issn | 1550-1477 |
language | English |
last_indexed | 2024-03-12T10:50:48Z |
publishDate | 2019-03-01 |
publisher | Hindawi - SAGE Publishing |
record_format | Article |
series | International Journal of Distributed Sensor Networks |
spelling | doaj.art-a3b8e497fe1943afb2818fdfa6c4db0b2023-09-02T06:59:25ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772019-03-011510.1177/1550147719839581An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networksJin Wang0Yu Gao1Wei Liu2Arun Kumar Sangaiah3Hye-Jin Kim4School of Information Science and Engineering, Fujian University of Technology, Fujian, ChinaCollege of Information Engineering, Yangzhou University, Yangzhou, ChinaCollege of Information Engineering, Yangzhou University, Yangzhou, ChinaSchool of Computing Science and Engineering, Vellore Institute of Technology (VIT), Vellore, IndiaBusiness Administration Research Institute, Sungshin Women’s University, Seoul, South KoreaNumerous tiny sensors are restricted with energy for the wireless sensor networks since most of them are deployed in harsh environments, and thus it is impossible for battery re-change. Therefore, energy efficiency becomes a significant requirement for routing protocol design. Recent research introduces data fusion to conserve energy; however, many of them do not present a concrete scheme for the fusion process. Emerging machine learning technology provides a novel direction for data fusion and makes it more available and intelligent. In this article, we present an intelligent data gathering schema with data fusion called IDGS-DF. In IDGS-DF, we adopt a neural network to conduct data fusion to improve network performance. First, we partition the whole sensor fields into several subdomains by virtual grids. Then cluster heads are selected according to the score of nodes and data fusion is conducted in CHs using a pretrained neural network. Finally, a mobile agent is adopted to gather information along a predefined path. Plenty of experiments are conducted to demonstrate that our schema can efficiently conserve energy and enhance the lifetime of the network.https://doi.org/10.1177/1550147719839581 |
spellingShingle | Jin Wang Yu Gao Wei Liu Arun Kumar Sangaiah Hye-Jin Kim An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks International Journal of Distributed Sensor Networks |
title | An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks |
title_full | An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks |
title_fullStr | An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks |
title_full_unstemmed | An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks |
title_short | An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks |
title_sort | intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks |
url | https://doi.org/10.1177/1550147719839581 |
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